I worked on on Text-To-Speech
for several years prior to coming to LTI. My general research
interests include pronunciation and acoustic modeling for speech
synthesis and recognition, efficient techniques for speech
recognition, and data-driven methods in linguistic analysis and
language processing.

My PhD advisor is Dr. Alex
Rudnicky. My research interests are presented below, or you can
also browse my Wiki. For the most
part, I work on acoustic and language modeling tools for the CMU Sphinx system. I am also
developing PocketSphinx, an
open-source speech recognition system for embedded and handheld
devices.

Research

Researchy things I'm interested in at the moment include but are by no
means limited to:

Distributed decoding algorithms for ASR and SMT. I'm interested
in building low-power personal recording devices which collaborate
over a wireless network in order to do speech recognition, information
extraction, machine translation, or what have you, in a meeting room
or lecture hall situation.

Speech recognition of spontaneous bilingual speech involving
code-switching. Aside from being an interesting test of multilingual
speech recognition, this is potentially useful for large parts of the
world where bilingualism (defined as being a native or near-native
speaker of multiple languages) is the norm rather than the
exception.

Efficient algorithms for on-line speaker adaptation. I'm
interested in strategies for performing vocal tract normalization and
acoustic model adaptation based on sufficient statistics that can be
collected and estimated with very little overhead compared to decoding
alone.

Methods for combining data from different channel conditions and
sampling rates in acoustic model training, and for dealing with
feature mismatches in decoding.

Figuring out what speech recognition (and by extension statistical
NLP) can learn from sociolinguistics and vice versa. It has often
seemed to me that these research communities are "speaking the same
language" in many ways, in that both accept variation as a fundamental
fact of naturalistic spoken language, and both are interested in
modeling it using statistical techniques. For further food for
thought, William Labov's paper on Quantitative
Reasoning in Linguistics may be of interest.